Our understanding of the scope and clinical relevance of gut microbiota metabolism of drugs is limited to relatively few biotransformations targeting a subset of therapeutics. Translating microbiome ...research into the clinic requires, in part, a mechanistic and predictive understanding of microbiome-drug interactions. This review provides an overview of microbiota chemistry that shapes drug efficacy and toxicity. We discuss experimental and computational approaches that attempt to bridge the gap between basic and clinical microbiome research. We highlight the current landscape of preclinical research focused on identifying microbiome-based biomarkers of patient drug response and we describe clinical trials investigating approaches to modulate the microbiome with the goal of improving drug efficacy and safety. We discuss approaches to aggregate clinical and experimental microbiome features into predictive models and review open questions and future directions toward utilizing the gut microbiome to improve drug safety and efficacy.
Gut microorganisms modulate host phenotypes and are associated with numerous health effects in humans, ranging from host responses to cancer immunotherapy to metabolic disease and obesity. However, ...difficulty in accurate and high-throughput functional analysis of human gut microorganisms has hindered efforts to define mechanistic connections between individual microbial strains and host phenotypes. One key way in which the gut microbiome influences host physiology is through the production of small molecules
, yet progress in elucidating this chemical interplay has been hindered by limited tools calibrated to detect the products of anaerobic biochemistry in the gut. Here we construct a microbiome-focused, integrated mass-spectrometry pipeline to accelerate the identification of microbiota-dependent metabolites in diverse sample types. We report the metabolic profiles of 178 gut microorganism strains using our library of 833 metabolites. Using this metabolomics resource, we establish deviations in the relationships between phylogeny and metabolism, use machine learning to discover a previously undescribed type of metabolism in Bacteroides, and reveal candidate biochemical pathways using comparative genomics. Microbiota-dependent metabolites can be detected in diverse biological fluids from gnotobiotic and conventionally colonized mice and traced back to the corresponding metabolomic profiles of cultured bacteria. Collectively, our microbiome-focused metabolomics pipeline and interactive metabolomics profile explorer are a powerful tool for characterizing microorganisms and interactions between microorganisms and their host.
It is well appreciated that microbial metabolism of drugs can influence treatment efficacy. Microbial β-glucuronidases in the gut can reactivate the excreted, inactive metabolite of irinotecan, a ...first-line chemotherapeutic for metastatic colorectal cancer. Reactivation causes adverse drug responses, including severe diarrhea. However, a direct connection between irinotecan metabolism and the composition of an individual's gut microbiota has not previously been made. Here, we report quantitative evidence of inter-individual variability in microbiome metabolism of the inactive metabolite of irinotecan to its active form. We identify a high turnover microbiota metabotype with potentially elevated risk for irinotecan-dependent adverse drug responses. We link the high turnover metabotype to unreported microbial β-glucuronidases; inhibiting these enzymes may decrease irinotecan-dependent adverse drug responses in targeted subsets of patients. In total, this study reveals metagenomic mining of the microbiome, combined with metabolomics, as a non-invasive approach to develop biomarkers for colorectal cancer treatment outcomes.
Gut microbiota metabolism of dietary compounds generates a vast array of microbiome-dependent metabolites (MDMs), which are highly variable between individuals. The uremic MDMs (uMDMs) ...phenylacetylglutamine (PAG), p-cresol sulfate (PCS), and indoxyl sulfate (IS) accumulate during renal failure and are associated with poor outcomes. Targeted dietary interventions may reduce toxic MDM generation; however, it is unclear if inter-individual differences in diet or gut microbiome dominantly contribute to MDM variance. Here, we use a 7-day homogeneous average American diet to standardize dietary precursor availability in 21 healthy individuals. During dietary homogeneity, the coefficient of variation in PAG, PCS, and IS (primary outcome) did not decrease, nor did inter-individual variation in most identified metabolites; other microbiome metrics showed no or modest responses to the intervention. Host identity and age are dominant contributors to variability in MDMs. These results highlight the potential need to pair dietary modification with microbial therapies to control MDM profiles.
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•Diet homogeneity did not decrease inter-individual variability in uremic MDMs•Homogeneous diet results in reduction of interpersonal variation in hippuric acid•Host identity and age, but not diet, are dominant contributors to variability in MDMs
Guthrie et al. determine the extent to which diet or the gut microbiome contributes to interpersonal variation in microbiome-dependent metabolites that are high priority targets of nutritional strategies to minimize levels. Diet homogeneity decreases inter-individual variability in hippurate but not key uremic solutes phenylacetylglutamine, p-cresol sulfate, and indoxyl sulfate.
Consumer acceptance testing found wheat flour alternatives can be combined with rare sugars to create acceptable lower sugar, gluten-free muffins. Muffins were developed and optimized using an ...initial screening procedure. A simplex centroid mixture design defined combinations of wheat-flour alternates. Ninety-one randomized baked blends were analyzed and compared for physical and basic sensory attributes using numerical optimization techniques. Blends of almond flour, whey protein concentrate, and a 50/50 blend of oat fibre and resistant maltodextrin achieved desired structures for high-protein and high-fibre muffins. Combinations of non-dairy coconut creamer, whey protein concentrate, and the same blend of oat fibre and maltodextrin composed the high-fat variant. Optimized flour replacement blends enabled a sugar replacement comparison in a separate categorical design. Vanilla-flavored muffins formulated with monosaccharides (allulose or tagatose) or sucrose (as a control), had sweetness levels augmented with stevia to theoretically equivalent levels. Muffins with allulose or tagatose differed from those containing sucrose in water activity and crust colour (lightness, L*). Overall liking for sucrose substituted formulations compared favorably in a consumer acceptance panel (n = 58). After providing the nutritional composition for sampled products at the conclusion of the sensory analysis, purchase intent of sugar substituted products was comparable to the control muffins.
•Evaluated combinations of seven wheat flour replacement ingredients in gluten-free muffins.•Mixed design optimized formulations with acceptable sensory and physiochemical properties.•Flour replacements selected for three nutrition profiles (high-protein, -fibre or -fat).•Use of allulose or tagatose in gluten-free muffins showed increased crust browning.•Purchase intent was equivalent following disclosure of product-specific nutritional profiles.
Practical Applications: Selection of flour alternatives using a mixture design for low-carbohydrate baked goods sweetened with rare sugars supports the potential of these ingredients in novel formulations.
The single-celled, multi-species communities of microbes that inhabit the human gastrointestinal tract are key contributors to how we respond to therapeutic drugs; but we have an incomplete ...understanding of the scope and mechanisms of their contributions to drug metabolism, efficacy and toxicity. The translational implications of a predictive and mechanistic understanding of microbiome-drug interactions range from precise biomarkers of patient adverse drug response (ADR) risk to the development of microbiota-targeted therapies that improve patient outcomes. Microbial enzymes from common gut colonists have been experimentally demonstrated to directly or indirectly impact the metabolism and efficacy of over 50 therapeutic drugs, driving inter-patient variability in drug activation, inactivation and toxicity. As an example, microbial β-glucuronidase activity drives the toxicity of a metastatic colorectal cancer chemotherapeutic and prodrug called Irinotecan (CPT-11). However, for CPT-11 and most microbiome influenced therapeutic drugs, which or whether human microbiome species or gene-level features predict patient response is not understood. Currently, a major obstacle in the field is that linking drug-microbiota interactions to targetable microbial enzymes or species is stymied by a lack of systematic knowledge of microbiota-drug interactions as well as a lack of quantitative, experimentally validated evidence of inter-individual variability in microbiome metabolism of therapeutic drugs. To address this obstacle, here I develop a multiscale experimental and computational framework to characterize gut microbiome derived signatures that predict differences in efficacy and ADRs relating to therapeutic drugs in individuals. I quantify inter-personal variation in drug metabolizing phenotypes or metabotypes via non-invasive fecal sampling and propose metagenomic biomarkers of high and low drug metabolism phenotypes. These approaches are used to gain insight into my long-term goals to 1) identify the level of biological complexity at which the microbiome is informative of patient therapeutic drug response outcomes; and 2) to gain a predictive understanding of the human gut microbiome drivers of interpersonal variation in drug and food metabolism and toxicity. In Chapter 1, I describe the impressive range of microbial metabolism and functions as well as the tools enabling current efforts to interrogate and predict the role of the gut microbiome in drug metabolism. I also introduce CPT-11 metabolism and the interconversion between its key active metabolite, SN-38, and inactive metabolite, SN-38 glucuronide (SN-38G), as a model to interrogate microbiome-drug interactions. In Chapter 2 of my thesis work, I link SN-38G metabolism to specific gut microbiome enzymes and transporters using metabolomic analyses of ex vivo administration of SN-38G to healthy participant fecal samples and shotgun metagenomics. In Chapter 3 I define the variability in metabolic response to the glucuronidated metabolite of the Nonsteroidal anti-inflammatory drug, indomethacin, in healthy and mCRC patient fecal microbiomes using targeted metabolomic analyses. In Chapter 4, I focus on MicrobeFDT, a graph database and resource for the inference of microbiome links to gastrointestinal tract food and drug chemical space. In Chapter 5, I demonstrate the use of MicrobeFDT towards the goal of identifying low toxicity food and drug based antibiotic sensitizing agents to improve the treatment of multidrug resistant gram-negative infections. Finally, in Chapter 6 I propose a path between our current understanding of the ecology and chemistry of gut microbiomes and engineering targeted changes to the gut microbial community to promote human health.
The objective of this research was to compare the efficacy of vacuuming, power blowing, and pressure washing for cleaning of a clogged pervious concrete pavement at a site in northern Utah. The ...results indicate that, for conditions similar to those evaluated, only pressure washing in conjunction with vacuuming can successfully clean clogged pervious concrete. In this research, an average water infiltration rate of 127 in./hour was achieved after cleaning. While the use of pervious concrete has many advantages, the cost of regularly cleaning pervious concrete pavement should be weighed against the cost of installing and maintaining a traditional detention basin for storm water management.
The selective inhibition of bacterial β-glucuronidases was recently shown to alleviate drug-induced gastrointestinal toxicity in mice, including the damage caused by the widely used anticancer drug ...irinotecan. Here, we report crystal structures of representative β-glucuronidases from the Firmicutes Streptococcus agalactiae and Clostridium perfringens and the Proteobacterium Escherichia coli, and the characterization of a β-glucuronidase from the Bacteroidetes Bacteroides fragilis. While largely similar in structure, these enzymes exhibit marked differences in catalytic properties and propensities for inhibition, indicating that the microbiome maintains functional diversity in orthologous enzymes. Small changes in the structure of designed inhibitors can induce significant conformational changes in the β-glucuronidase active site. Finally, we establish that β-glucuronidase inhibition does not alter the serum pharmacokinetics of irinotecan or its metabolites in mice. Together, the data presented advance our in vitro and in vivo understanding of the microbial β-glucuronidases, a promising new set of targets for controlling drug-induced gastrointestinal toxicity.
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•Microbiome drug targets are examined from Firmicutes and Bacteroides•Marked differences seen in catalytic activities and propensities for inhibition•Inhibition does not alter serum pharmacokinetics of irinotecan or its metabolites•Phylogeny defines major enzyme groups guided by structural features
Wallace et al. elucidate the structure and function of enzymes from the major gastrointestinal microbiome phyla that when selectively targeted by potent inhibitors can uniquely control the side effects of a cancer chemotherapeutic.
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